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GOSSYPIUM PLANT DISEASE DECTECTION AND PREDICTIONS
ISSN: 2582 - 9130
Publisher: author
GOSSYPIUM PLANT DISEASE DECTECTION AND PREDICTIONS
Indexed in
Educational Science
ARTICLE-FACTOR
1.3
Article Basics Score: 3
Article Transparency Score: 2
Article Operation Score: 2
Article Articles Score: 3
Article Accessibility Score: 3
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International Category Code (ICC):
ICC-1502
Publisher: Krishma Publication
International Journal Address (IAA):
IAA.ZONE/2582383899130
eISSN
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2582 - 9130
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Abstract
India is the leading country in the world which produce Cotton. Cotton crops are damaged due to early fall off leaf or leaf will get infected due to diseases. Various climatic conditions like scorching temperature in crop field and also some pesticides will be required within time, numerous diseases like bacterial blights, alternaria, etc can be detect by multiple system through soil monitoring. After disease detection, will be provided to the farmers using various deep learing algorithms and IoT-based system. The deep CNN model is developed to perform cotton plant disease detection using infected and healthy cotton leaf images by collecting images through the complete process used in training and validation for image pre-processing; augmentation and fine-tuning. Different test cases were accomplished to check the performance of the created model and make this new system economical and independent. This newly created system gives accu...
